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Clutter Suppression for Indoor Self-Localization Systems by Iteratively Reweighted Low-Rank Plus Sparse Recovery
Jesús Sánchez-Pastor1, Udaya S K P Miriya Thanthrige2, Furkan Ilgac2
1Institute of Microwave Engineering and Photonics, Technical University of Darmstadt, 64283 Darmstadt, Germany.
Sensors (Basel, Switzerland)
|October 26, 2021
Summary
A novel iterative algorithm using low-rank plus sparse recovery (RPCA) effectively suppresses clutter in passive RFID-based self-localization. This method significantly improves tag detection, especially for low-Q tags, outperforming traditional time-gating techniques.
Area of Science:
- Electrical Engineering and Computer Science
- Signal Processing
- Robotics and Automation
Background:
- Passive RFID-based self-localization offers numerous applications but faces significant challenges due to strong clutter signals.
- Clutter echoes often overwhelm the weaker backscattered signals from passive tag landmarks, hindering accurate localization.
- Distinguishing between low-Q (broad frequency response) and high-Q (sparse frequency response) tags is crucial for effective signal processing.
Purpose of the Study:
- To develop and evaluate an iterative algorithm for mitigating clutter and retrieving passive RFID tag responses.
- To compare the proposed algorithm's performance against the established time-gating technique for self-localization scenarios.
- To enhance the reliability and accuracy of passive indoor self-localization systems.
Main Methods:
- Implementation of an iterative algorithm based on a low-rank plus sparse recovery (RPCA) approach.
- Analysis of two tag types: low-Q tags with broad frequency response and high-Q tags with sparse frequency response.
- Comparative performance evaluation against the time-gating technique under varying clutter conditions.
Main Results:
- The proposed RPCA algorithm significantly outperforms time-gating for low-Q tags, enabling successful clutter suppression and tag identification.
- RPCA effectively handles scenarios where clutter overlaps with the time-gating window.
- For high-Q tags, RPCA increases the backscattered power at resonance by approximately 12 dB at 80 cm.
Conclusions:
- The low-rank plus sparse recovery (RPCA) approach is a highly promising method for improving passive RFID-based self-localization.
- RPCA offers superior clutter mitigation and tag identification capabilities compared to time-gating, particularly for low-Q tags.
- This technique enhances the robustness and performance of indoor localization systems utilizing passive RFID tags.
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